This paper presents keyword extraction using lexical chains and graph centrality measures, derived from the semantic similarity of the words by analysis of the graphical network created using WordNet. The hypothesis is presented using a small-world approach where every paragraph in a document is constrained to a local point, while the document in all is centered on a global concept. Creating lexical chains for each paragraph and combining the best via scoring methods and graph based algorithms, we present parallels to baseline system to extract the keywords from the document.

Graph centrality, keyword extraction, lexical chains, semantic similarity, small world approach, WordNet.